A chance constrained dynamic network reconfiguration based on Minty algorithm in distribution networks

With high renewable energy sources (RESs) penetration in distribution networks, handling the uncertainties of RESs outputs and multi-time coupling problems in the dynamic network reconfiguration (DNR) is a big challenge. Besides, the existing mathematical and artificial intelligence algorithms for n...

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Bibliographic Details
Published in:Applied mathematics and nonlinear sciences Vol. 9; no. 1
Main Authors: Song, Xinfu, Li, Changling, Yi, Geng, Zhong, Rui, Wang, Wei
Format: Journal Article
Language:English
Published: Beirut Sciendo 01.01.2024
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
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ISSN:2444-8656, 2444-8656
Online Access:Get full text
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Summary:With high renewable energy sources (RESs) penetration in distribution networks, handling the uncertainties of RESs outputs and multi-time coupling problems in the dynamic network reconfiguration (DNR) is a big challenge. Besides, the existing mathematical and artificial intelligence algorithms for network reconfiguration face the problem of falling into local optima and poor convergence. To address the above challenge and problem, this paper first establishes a chance-constrained programming model to handle the uncertainties. Then the Minty algorithm is applied for efficiency and accurate static network reconfiguration (SNR) in each time interval. Finally, a branch exchange-based method is proposed to eliminate violations for the operation times of switches. Numerical simulations on the IEEE 33 system and an actual 151-bus distribution network show the superiority of the proposed algorithm over existing methods.
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ISSN:2444-8656
2444-8656
DOI:10.2478/amns.2023.2.00304